A fuzzy analytic hierarchy process (AHP)/data envelopment analysis (DEA) hybrid model for efficiently allocating energy R&D resources: In the case of energy technologies against high oil prices

  • Lee S
  • Mogi G
  • Hui K
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Abstract

The Low Carbon, Green Growth was declared as Korean national agenda in 2008. Korea has been enhancing the green growth for the sustainable economic development and fostering energy. To improve Korean national energy security and promote the Low Carbon, Green Growth, we established a long term strategic energy technology roadmap. In this paper, five criteria, such as economical impact, commercial potential, inner capacity, technical spin-off, and development cost, were used to assess the strategic energy technologies against high oil prices. We developed the integrated two-stage multi-criteria decision making (MCDM) approach which was used to evaluate the relative weights of criteria and measures the relative efficiency of energy technologies against high oil prices. On the first stage, the fuzzy analytic hierarchy process, reflecting the vagueness of human thought with interval values instead of crisp numbers, allocated the relative weights of criteria effectively instead of the AHP approach. On the second stage, the data envelopment analysis approach measured the relative efficiency of energy technologies against high oil prices with economic viewpoints. The relative efficiency score of energy technologies against high oil prices can be the fundamental decision making data which help decision markers to effectively allocate the limited R&D resources. © 2013 Elsevier Ltd.

Author-supplied keywords

  • DEA
  • Energy technology R&D plan
  • Fuzzy AHP

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